How to assess the needs of vulnerable population groups towards heat-sensitive routing? An evidence-based and practical approach to reducing urban heat stress

Geo-spatial Information Science

OpenStreetMap (OSM) is a dataset in constant change and this dynamic needs to be better understood. Based on 12-year time series of seven OSM data contribution activities extracted from 20 large cities worldwide, we investigate the temporal dynamic of OSM data production, more specifically, the auto- and cross-correlation, temporal trend, and annual seasonality of these activities. Furthermore, we evaluate and compare nine different temporal regression methods for forecasting such activities in horizons of 1–4 weeks. Several insights could be obtained from our analyses, including that the contribution activities tend to grown linearly in a moderate intra-annual cycle. Also, the performance of the temporal forecasting methods shows that they yield in general more accurate estimations of future contribution activities than a baseline metric, i.e. the arithmetic average of recent previous observations. In particular, the …

arXiv preprint arXiv:2401.04218

We present a benchmark for assessing the capability of Large Language Models (LLMs) to discern intercardinal directions between geographic locations and apply it to three prominent LLMs: GPT-3.5, GPT-4, and Llama-2. This benchmark specifically evaluates whether LLMs exhibit a hierarchical spatial bias similar to humans, where judgments about individual locations' spatial relationships are influenced by the perceived relationships of the larger groups that contain them. To investigate this, we formulated 14 questions focusing on well-known American cities. Seven questions were designed to challenge the LLMs with scenarios potentially influenced by the orientation of larger geographical units, such as states or countries, while the remaining seven targeted locations less susceptible to such hierarchical categorization. Among the tested models, GPT-4 exhibited superior performance with 55.3% accuracy, followed by GPT-3.5 at 47.3%, and Llama-2 at 44.7%. The models showed significantly reduced accuracy on tasks with suspected hierarchical bias. For example, GPT-4's accuracy dropped to 32.9% on these tasks, compared to 85.7% on others. Despite these inaccuracies, the models identified the nearest cardinal direction in most cases, suggesting associative learning, embodying human-like misconceptions. We discuss the potential of text-based data representing geographic relationships directly to improve the spatial reasoning capabilities of LLMs.

HEUREKA'24-Optimierung in Verkehr und Transport, Stuttgart, 13rd-14th March 2024

Zur Beschreibung der Attraktivität von Gebieten im Rahmen der Zielwahlmodellierung werden oftmals Informationen über Points-of-Interest (POI) aus OpenStreetMap (OSM) genutzt. Wir haben die Vollständigkeit der OSM-POI-Datenbank für 129 Untersuchungsgebiete mithilfe von Vollerhebungen geprüft. Die Vollständigkeit der OSM-Datenbank unterscheidet sich zwischen einzelnen Kategorien erheblich. OSM ist in den Kategorien Gastronomie und Einzelhandel in weiten Teilen vollständig und nach stichprobenartiger Prüfung im Anwendungsfall für die Modellierung nutzbar. In den Kategorien Dienstleistung mit Kundenverkehr und Medizinische Versorgung fehlen in OSM zumeist eine Vielzahl an POI. Strukturelle Einflüsse räumlicher oder intrinsischer Indikatoren konnten nicht nachgewiesen werden.

Nature Communications

OpenStreetMap (OSM) has evolved as a popular dataset for global urban analyses, such as assessing progress towards the Sustainable Development Goals. However, many analyses do not account for the uneven spatial coverage of existing data. We employ a machine-learning model to infer the completeness of OSM building stock data for 13,189 urban agglomerations worldwide. For 1,848 urban centres (16% of the urban population), OSM building footprint data exceeds 80% completeness, but completeness remains lower than 20% for 9,163 cities (48% of the urban population). Although OSM data inequalities have recently receded, partially as a result of humanitarian mapping efforts, a complex unequal pattern of spatial biases remains, which vary across various human development index groups, population sizes and geographic regions. Based on these results, we provide recommendations for data …

Proceedings of the OSM Science

Advances in Artificial Intelligence (AI) and, specifically, in Deep Learning (DL) have fostered geospatial analysis and remote sensing, culminating in the establishment of GeoAI [1, 2] and the solidification of research on methodologies and techniques for AI-assisted mapping [3-7]. Nevertheless, a particular challenge lies in the substantial demand for training examples in DL. Manual labelling of these examples is labour-intensive, consuming a considerable amount of time and financial resources. Alternatively, semi or automated labelling of data emerges as a prominent solution, as exemplified by the tool ohsome2label [8], which harnesses data from the OpenStreetMap [9] to label satellite images. However, moving from characterising object types (road, river, building) based on geometry to categorising them by attributes might result in an imbalanced class distribution in the utilised Machine Learning (ML) dataset.Such imbalances are common in numerous practical applications. Learning from skewed datasets can be particularly challenging and often requires non-conventional ML techniques. A comprehensive awareness of the issues associated with class imbalance, as well as strategies for mitigating them, is essential [10]. In the context of spatial data, the distribution of classes can vary from country to country and region to region, adding a new layer of complexity and exacerbating this issue. In this context, an analysis was conducted on the distribution of road types, defined by the values of the OSM" highway" tag, in diverse-profile nations. The aim was to evaluate the extent of class imbalance and to identify any consistent patterns in the …

Environmental Monitoring and Assessment

Spatially explicit information on carbon fluxes related to land use and land cover change (LULCC) is of value for the implementation of local climate change mitigation strategies. However, estimates of these carbon fluxes are often aggregated to larger areas. We estimated committed gross carbon fluxes related to LULCC in Baden-Württemberg, Germany, using different emission factors. In doing so, we compared four different data sources regarding their suitability for estimating the fluxes: (a) a land cover dataset derived from OpenStreetMap (OSMlanduse); (b) OSMlanduse with removal of sliver polygons (OSMlanduse cleaned), (c) OSMlanduse enhanced with a remote sensing time series analysis (OSMlanduse+); (d) the LULCC product of Landschaftsveränderungsdienst (LaVerDi) from the German Federal Agency of Cartography and Geodesy. We produced a high range of carbon flux estimates, mostly caused …

ISPRS International Journal of Geo-Information

Natural hazards threaten millions of people all over the world. To address this risk, exposure and vulnerability models with high resolution data are essential. However, in many areas of the world, exposure models are rather coarse and are aggregated over large areas. Although OpenStreetMap (OSM) offers great potential to assess risk at a detailed building-by-building level, the completeness of OSM building footprints is still heterogeneous. We present an approach to close this gap by means of crowd-sourcing based on the mobile app MapSwipe, where volunteers swipe through satellite images of a region collecting user feedback on classification tasks. For our application, MapSwipe was extended by a completeness feature that allows to classify a tile as “no building”, “complete” or “incomplete”. To assess the quality of the produced data, the completeness feature was applied to four regions. The MapSwipe-based assessment was compared with an intrinsic approach to quantify completeness and with the prediction of an existing model. Our results show that the crowd-sourced approach yields a reasonable classification performance of the completeness of OSM building footprints. Results showed that the MapSwipe-based assessment produced consistent estimates for the case study regions while the other two approaches showed a higher variability. Our study also revealed that volunteers tend to classify nearly completely mapped tiles as “complete”, especially in areas with a high OSM building density. Another factor that influenced the classification performance was the level of alignment of the OSM layer with the satellite imagery.

Engineering Proceedings

Urban heat islands, characterized by higher temperatures in cities compared to surrounding areas, have been studied using various techniques. However, during heat waves, existing models often underestimate the intensity of these heat islands compared to empirical measurements. To address this, an hourly time-series-based model for predicting heat island intensity during heat wave conditions is proposed. The model was developed and validated using empirical data from the National Monitoring Network in Temuco, Chile. Results indicate a strong correlation (r > 0.98) between the model’s predictions and actual monitoring data. Additionally, the study emphasizes the importance of considering the unique microclimatic characteristics and built environment of each city when modelling urban heat islands. Factors such as urban morphology, land cover, and anthropogenic heat emissions interact in complex ways, necessitating tailored modelling approaches for the accurate representation of heat island phenomena.

Environmental Monitoring and Assessment

Spatially explicit information on carbon fluxes related to land use and land cover change (LULCC) is of value for the implementation of local climate change mitigation strategies. However, estimates of these carbon fluxes are often aggregated to larger areas. We estimated committed gross carbon fluxes related to LULCC in Baden-Württemberg, Germany, using different emission factors. In doing so, we compared four different data sources regarding their suitability for estimating the fluxes: (a) a land cover dataset derived from OpenStreetMap (OSMlanduse); (b) OSMlanduse with removal of sliver polygons (OSMlanduse cleaned), (c) OSMlanduse enhanced with a remote sensing time series analysis (OSMlanduse+); (d) the LULCC product of Landschaftsveränderungsdienst (LaVerDi) from the German Federal Agency of Cartography and Geodesy. We produced a high range of carbon flux estimates, mostly caused …

Communications Earth & Environment

Individual behavior plays a pivotal role in mitigating climate change but our understanding of the multifaceted, determining factors of sustainable behavior remains incomplete. Here we conducted a comprehensive, cross-sectional survey of German households in 2021 (N = 10,813), assessing various potential determinants and measuring behavior in greenhouse gas emissions across various life domains (shelter, mobility, consumption, and diet). Machine learning models were employed to predict emissions from determining factors and benchmarked against commonly used linear models. Our findings indicate that machine learning models excel in capturing complex relationships between personal and situational factors, offering a more nuanced understanding of how determinants interplay and contribute to emissions. Notably, some factors like perceived behavioral control or habits consistently affected …

Proceedings of the OSM Science

1 GIScience Research Group, Heidelberg University, Heidelberg, Germany; francis. andorful@ uni-heidelberg. de, nir. fulman@ uni-heidelberg. de 2 HeiGIT-Heidelberg Institute for Geoinformation Technology, 69120 Heidelberg, Germany; sven. lautenbach@ uni-heidelberg. de, christina. ludwing@ uni-heidelberg. de, herfort@ uni-heidelberg. de, zipf@ uni-heidelberg. de

International Journal of Applied Earth Observation and Geoinformation

The disease transmitting mosquito Aedes Aegypti is an increasing global threat. It breeds in small artificial containers such as rainwater tanks and can be characterized by a short flight range. The resulting high spatial variability of abundance is challenging to model. Therefore, we tested an approach to map water tank density as a spatial proxy for urban Aedes Aegypti habitat suitability. Water tank density mapping was performed by a semi-supervised self-training approach based on open accessible satellite imagery for the city of Rio de Janeiro. We ran a negative binomial generalized linear regression model to evaluate the statistical significance of water tank density for modeling inner-urban Aedes Aegypti distribution measured by an entomological surveillance system between January 2019 and December 2021. Our proposed semi-supervised model outperformed a supervised model for water tank detection …

Nature Communications

OpenStreetMap (OSM) has evolved as a popular dataset for global urban analyses, such as assessing progress towards the Sustainable Development Goals. However, many analyses do not account for the uneven spatial coverage of existing data. We employ a machine-learning model to infer the completeness of OSM building stock data for 13,189 urban agglomerations worldwide. For 1,848 urban centres (16% of the urban population), OSM building footprint data exceeds 80% completeness, but completeness remains lower than 20% for 9,163 cities (48% of the urban population). Although OSM data inequalities have recently receded, partially as a result of humanitarian mapping efforts, a complex unequal pattern of spatial biases remains, which vary across various human development index groups, population sizes and geographic regions. Based on these results, we provide recommendations for data …

npj Climate Action

On the path towards net zero emissions in academia, reducing flight emissions is of high importance, yet particularly difficult to achieve. Flight emissions have a major share of the total greenhouse gas (GHG) emissions of research institutions but reducing them is challenging, because flying has become an essential part of academic culture. While there is a large amount of literature on the relevance of flight reduction in academia, very little data and hands-on experience exists on what a successful reduction process might entail. This paper contributes to closing this gap by presenting data from interviews and surveys from eight academic institutions on reasons for air travel and alternatives, showing how a transdisciplinary approach can support a transformation from a high to a low flying culture, and suggesting a practical path forward with the aid of an open-access toolbox on how to reduce flight emissions in …

This discussion paper originated as the concluding publication of one of the pilot projects of the "Climate Action Science" research initiative at Heidelberg Center for the Environment (HCE), focusing on the Rhine-Neckar district and the city of Heidelberg. The aim of the explorative project was to generate a first overview on greenhouse gas emission data in order to initiate climate action of various actors and to provide well-founded support by using accurate infor-mation. The focus during the pilot phase was on the collection, compilation and evaluation of the quality of heterogeneous data sets and methods for a greenhouse gas emission inventory, as well as on the information preparation and evaluation of different inventory and presentation options. These should in turn be adapted to the needs of different users and fields of applica-tion. The study focused on different German approaches to greenhouse gas accounting, espe-cially in Baden-Württemberg compared to other German states, and in detail on the City of Heidelberg compared to the surrounding municipalities in the Rhine-Neckar district. The over-arching goal is to use the results beyond the case study projected here as a stimulus and pre-liminary work for further projects and activities in the overall "Climate Action Science" project. Several difficulties were encountered in processing the emissions inventory and compiling var-ious data sets on emissions in the study area. Three basic situations were identified: 1. De-sired data is not available (measurements required), 2. Desired data is not freely accessible (stakeholder involvement), 3. Data generation via proxy data. In the pilot phase …

European Neuropsychopharmacology

The COVID-19 pandemic strongly impacted people's daily lives. However, it remains unknown how the pandemic situation affects daily-life experiences of individuals with preexisting severe mental illnesses (SMI). In this real-life longitudinal study, the acute onset of the COVID-19 pandemic in Germany did not cause the already low everyday well-being of patients with schizophrenia (SZ) or major depression (MDD) to decrease further. On the contrary, healthy participants’ well-being, anxiety, social isolation, and mobility worsened, especially in healthy individuals at risk for mental disorder, but remained above the levels seen in patients. Despite being stressful for healthy individuals at risk for mental disorder, the COVID-19 pandemic had little additional influence on daily-life well-being in psychiatric patients with SMI. This highlights the need for preventive action and targeted support of this vulnerable population.

Transportation Research Record

OpenStreetMap (OSM) data are geographical data that are easy and open to access and therefore used for a large set of applications including travel demand modeling. However, often there is a limited awareness about the shortcomings of volunteered geographic information data, such as OSM. One important issue for the application in travel demand modeling is the completeness of OSM elements, particularly points of interest (POI), since it directly influences the predictions of trip distributions. This might cause unreliable model sensitivities and end up in wrong predictions leading to expensive misinterpretations of the effects of policy measures. Because of a lack of large-scale real-world data, a detailed assessment of the quality of POI from OSM has not been done yet. Therefore, in this work, we assess the quality of POI from OSM for use within travel demand models using surveyed real-world data from 49 areas …

ERDKUNDE

Environmental change is increasingly challenging the habitability of places around the world, particularly with regard to resource-dependent rural areas in the Global South. Apart from objectively measurable, bio-physical indices, it is likewise important to look at individual and group-specific perceptions of habitability, which are embedded in their respective socio-cultural context (s). Migration as a well-established household risk diversification strategy has the potential to increase people’s adaptive capacity, their well-being, and can shape the way people perceive the habitability of places. This study utilizes a human-centered approach in order to unravel the impacts of migration on culturally-embedded and subjective perceptions of habitability in a rural community in Northern Ghana which faces increasing pressure of environmental changes. Based on qualitative empirical research, we utilize place attachment, social status, and community cohesion as exemplary socio-cultural dimensions with particular relevance in this specific local context to showcase 1) the subjectivity and cultural embeddedness of habitability perceptions and 2) the respective potential of migration to influence such perceptions to both positive and negative ends. Positive migration impacts on the underlying socio-cultural context (s) can serve to undergird (collective) responsibility and adaptive action towards improving local habitability in parallel to encouraging efforts that strive to maintain cultural integrity. Integrating this knowledge in future habitability assessments can pave the way for context-sensitive and locally-adjusted resilience-building strategies that take the …

Erdkunde

This paper uses the concept of riskscapes to understand the way climate risks manifest themselves and interact with other risks to create vulnerable local communities in Ethiopia and Tanzania. The main research question we addressed is: what are the different sources of risks facing farmers' livelihoods in the selected case study areas of both countries and where does climate risk fit? The study uses qualitative research methodology with thick description of our case studies to identify variables which are common in both countries. Accordingly, we identified six major risk settings which are important in determining the vulnerability of communities, namely 'climate hazard risk setting', 'subsistence risk setting', 'population increase risk setting', 'state policy failure risk setting', 'market volatility risk setting', and 'supernatural risk setting'. Our findings highlight two important points. First, the interaction between risk settings …

Erdkunde

This paper uses the concept of riskscapes to understand the way climate risks manifest themselves and interact with other risks to create vulnerable local communities in Ethiopia and Tanzania. The main research question we addressed is: what are the different sources of risks facing farmers' livelihoods in the selected case study areas of both countries and where does climate risk fit? The study uses qualitative research methodology with thick description of our case studies to identify variables which are common in both countries. Accordingly, we identified six major risk settings which are important in determining the vulnerability of communities, namely 'climate hazard risk setting', 'subsistence risk setting', 'population increase risk setting', 'state policy failure risk setting', 'market volatility risk setting', and 'supernatural risk setting'. Our findings highlight two important points. First, the interaction between risk settings …

ERDKUNDE

Environmental change is increasingly challenging the habitability of places around the world, particularly with regard to resource-dependent rural areas in the Global South. Apart from objectively measurable, bio-physical indices, it is likewise important to look at individual and group-specific perceptions of habitability, which are embedded in their respective socio-cultural context (s). Migration as a well-established household risk diversification strategy has the potential to increase people’s adaptive capacity, their well-being, and can shape the way people perceive the habitability of places. This study utilizes a human-centered approach in order to unravel the impacts of migration on culturally-embedded and subjective perceptions of habitability in a rural community in Northern Ghana which faces increasing pressure of environmental changes. Based on qualitative empirical research, we utilize place attachment, social status, and community cohesion as exemplary socio-cultural dimensions with particular relevance in this specific local context to showcase 1) the subjectivity and cultural embeddedness of habitability perceptions and 2) the respective potential of migration to influence such perceptions to both positive and negative ends. Positive migration impacts on the underlying socio-cultural context (s) can serve to undergird (collective) responsibility and adaptive action towards improving local habitability in parallel to encouraging efforts that strive to maintain cultural integrity. Integrating this knowledge in future habitability assessments can pave the way for context-sensitive and locally-adjusted resilience-building strategies that take the …

ERDKUNDE

Heat poses a significant risk to human health, particularly for vulnerable populations, such as pregnant women, older individuals, young children and people with pre-existing medical conditions. In view of this, we formulated a heat stress-avoidant routing approach in Heidelberg, Germany, to ensure mobility and support day-to-day activities in urban areas during heat events. Although the primary focus is on pedestrians, it is also applicable to cyclists. To obtain a nuanced understanding of the needs and demands of the wider population, especially vulnerable groups, and to address the challenge of reducing urban heat stress, we used an inter-and transdisciplinary approach. The needs of vulnerable groups, the public, and the city administration were identified through participatory methods and various tools, including interactive city walks. Solution approaches and adaptation measures to prevent heat stress were evaluated and integrated into the development of a heat-avoiding route service through a co-design process. The findings comprise the identification of perceived hotspots for heat (such as large public spaces in the city centre with low shading levels), the determination of commonly reported symptoms resulting from severe heat (eg, fatigue or lack of concentration), and the assessment of heat adaptation measures that were rated positively, including remaining in the shade and delaying errands. Additionally, we analysed and distinguished between individual and community adaptation strategies. Overall, many respondents did not accurately perceive the risk of heat stress in hot weather, despite severe limitations. As a result, the heat …

ERDKUNDE

Environmental change is increasingly challenging the habitability of places around the world, particularly with regard to resource-dependent rural areas in the Global South. Apart from objectively measurable, bio-physical indices, it is likewise important to look at individual and group-specific perceptions of habitability, which are embedded in their respective socio-cultural context (s). Migration as a well-established household risk diversification strategy has the potential to increase people’s adaptive capacity, their well-being, and can shape the way people perceive the habitability of places. This study utilizes a human-centered approach in order to unravel the impacts of migration on culturally-embedded and subjective perceptions of habitability in a rural community in Northern Ghana which faces increasing pressure of environmental changes. Based on qualitative empirical research, we utilize place attachment, social status, and community cohesion as exemplary socio-cultural dimensions with particular relevance in this specific local context to showcase 1) the subjectivity and cultural embeddedness of habitability perceptions and 2) the respective potential of migration to influence such perceptions to both positive and negative ends. Positive migration impacts on the underlying socio-cultural context (s) can serve to undergird (collective) responsibility and adaptive action towards improving local habitability in parallel to encouraging efforts that strive to maintain cultural integrity. Integrating this knowledge in future habitability assessments can pave the way for context-sensitive and locally-adjusted resilience-building strategies that take the …

ERDKUNDE

Heat poses a significant risk to human health, particularly for vulnerable populations, such as pregnant women, older individuals, young children and people with pre-existing medical conditions. In view of this, we formulated a heat stress-avoidant routing approach in Heidelberg, Germany, to ensure mobility and support day-to-day activities in urban areas during heat events. Although the primary focus is on pedestrians, it is also applicable to cyclists. To obtain a nuanced understanding of the needs and demands of the wider population, especially vulnerable groups, and to address the challenge of reducing urban heat stress, we used an inter-and transdisciplinary approach. The needs of vulnerable groups, the public, and the city administration were identified through participatory methods and various tools, including interactive city walks. Solution approaches and adaptation measures to prevent heat stress were evaluated and integrated into the development of a heat-avoiding route service through a co-design process. The findings comprise the identification of perceived hotspots for heat (such as large public spaces in the city centre with low shading levels), the determination of commonly reported symptoms resulting from severe heat (eg, fatigue or lack of concentration), and the assessment of heat adaptation measures that were rated positively, including remaining in the shade and delaying errands. Additionally, we analysed and distinguished between individual and community adaptation strategies. Overall, many respondents did not accurately perceive the risk of heat stress in hot weather, despite severe limitations. As a result, the heat …

ERDKUNDE

Heat poses a significant risk to human health, particularly for vulnerable populations, such as pregnant women, older individuals, young children and people with pre-existing medical conditions. In view of this, we formulated a heat stress-avoidant routing approach in Heidelberg, Germany, to ensure mobility and support day-to-day activities in urban areas during heat events. Although the primary focus is on pedestrians, it is also applicable to cyclists. To obtain a nuanced understanding of the needs and demands of the wider population, especially vulnerable groups, and to address the challenge of reducing urban heat stress, we used an inter-and transdisciplinary approach. The needs of vulnerable groups, the public, and the city administration were identified through participatory methods and various tools, including interactive city walks. Solution approaches and adaptation measures to prevent heat stress were evaluated and integrated into the development of a heat-avoiding route service through a co-design process. The findings comprise the identification of perceived hotspots for heat (such as large public spaces in the city centre with low shading levels), the determination of commonly reported symptoms resulting from severe heat (eg, fatigue or lack of concentration), and the assessment of heat adaptation measures that were rated positively, including remaining in the shade and delaying errands. Additionally, we analysed and distinguished between individual and community adaptation strategies. Overall, many respondents did not accurately perceive the risk of heat stress in hot weather, despite severe limitations. As a result, the heat …

Erdkunde

This methodological paper proposes two codifiability indicators to examine trade and manufacturing statistics and the spatial distribution of value-added manufacturing activities. Codifiability is defined as the level of documentation about the manufacturing processes of a product required to allow tasks to be replicated by other suppliers. First, the codifiability indicators allow researchers to examine products that are grouped under the same sub-product class in conventional statistics, but the manufacture of such products could involve vastly different technologies and thus the level of value-added. A proprietary database was used to delineate the supply networks of automakers in passenger vehicles and their major tier-I suppliers between 2000 and 2015. Second, codifiability allowed the researchers to unpack the spatial distribution of value-addedness of each supplier in the production network, as illustrated by the …

Erdkunde

Tropical highlands remain a challenging target for remote sensing due to their high heterogeneity of the landscape and frequent cloud cover, causing a shortage of high-quality and reliable comprehensive data on land use and land cover on a local or regional scale. These, however, are urgently needed by local stakeholders and decisionmakers. This applies for example to the Muringato sub-catchment in Nyeri County, Kenya, where acute water problems have been identified to be usually directly related to specific land use and land cover. This article contributes to the understanding of tropical highlands from a remote sensing perspective by examining Sentinel-1, Sentinel-2 and Global Forest Canopy Height Model data from the Global Ecosystem Dynamics Investigation, all provided by the Google Earth Engine. To do so, we assess classifiers derived from these datasets for different land cover types, analyzing the …

ERDKUNDE

This is a datapaper including microscopically measured data of annual ring widths from the Mediterranean-alpine shrub species Cytisus galianoi (Sierra Nevada, Spain). The dataset will be updated with future measurements.

ERDKUNDE

Here, we present a datapaper containing observational air quality and meteorological data related to our long-term air quality monitoring program at the UNESCO Natural World Heritage Site Geirangerfjord, Western Norway. The dataset will be updated with future data.

Erdkunde

Recent empirical research on internal migration has focused on the change in migration volume, before and after the outbreak of the COVID-19 pandemic, by the degree of urbanization. Less is known about the types of rural areas that are attracting internal migrants. This study aims to explore the changes in internal rural migration patterns in Serbia due to the COVID-19 pandemic, focusing on the types of rural settlements as places of destinations and types of urban settlements as places of the origin of migrants. Relying on the additionally processed official national annual statistical data for the period 2018–2021, we offer findings on the differences in volume and socio-demographic characteristics of migrants across six internal migration flows (from small towns, medium-sized towns, and large cities, to suburban and non-suburban rural settlements). The results reveal that the pandemic affected an increase of rural …

ERDKUNDE

Here we present a datapaper containing microscopically measured data of annual ring widths in the arctic-alpine dwarf-shrub species Salix herbacea (central Norway). The dataset will be updated with future measurements.

Erdkunde

In the Brazilian Amazon region, social, economic, and political changing structures have increased the pressure on land, generating inequalities for the region's most vulnerable residents. Simultaneously, scientific knowledge production has increased and documented the region's different realities. This document presents a scientific discourse analysis of land-use change in the Amazonian region and its interaction with socio-environmental (in) justice, considering the pluriversal perspective. We respond to the main questions: Do hierarchies in scientific knowledge production contribute to silencing subaltern voices and hiding a pluriverse approach when writing about Amazonia land issues? And if so, how? A systematic literature review was conducted using the scientific dissemination platforms Scielo, Scopus, and WoS. The results show a disproportionate representation of some stakeholders, and some states are used as near-total representatives for the Amazonia region. Furthermore, consideration of pluriversal perspectives in the articles does not guarantee high sensibility for heterogeneity of local contexts or for making subaltern voices heard.

Erdkunde

Terroir is a concept referring interactions of natural (topography, lithology, climate, soil etc.) and human (economic conditions, traditions, cultivation practices, etc.) factors; therefore, terroir is spatially delimited and subjected to environmental, socio-economic, and temporal changes. The geoecological background of wine districts are considered more stable among them, but, because of its natural diversity and the spatial changes of production sites, changes in abiotic terroir components might occur too. In this study the spatial changes of grape production sites in Eger Wine District (Hungary) across two and a half centuries (1784 to 2018), and their consequences on the composition of the geoecological factors (lithology, topography, soil characteristics) were analyzed. Modernization of cultivation, urbanization and increase of builtup areas around the central settlement resulted in decreased concentration, i.e …

ERDKUNDE

This is a datapaper including microscopically measured data of annual ring widths from the Mediterranean-alpine shrub species Cytisus galianoi (Sierra Nevada, Spain). The dataset will be updated with future measurements.

ERDKUNDE

Here, we present a datapaper containing observational air quality and meteorological data related to our long-term air quality monitoring program at the UNESCO Natural World Heritage Site Geirangerfjord, Western Norway. The dataset will be updated with future data.

Erdkunde

In disaster-prone countries, it is of great concern that societies as a whole, as well as households and individuals, should become as resilient to disasters as possible. In Myanmar, with its frequent natural hazards like floods, cyclones and droughts and its high probability of earthquakes, raising awareness of and preparedness for disasters is of eminent importance in order to increase the resilience of society, households and individuals. Disaster research shows that the awareness and perception of people regarding disasters and thus also their risk preparedness can vary substantially. This seems to stem from various sources: the socio-demographic characteristics of households and people as well as former experiences of disaster seem to play a crucial role. Information of such variables and understanding how they influence the disaster risk perception and preparedness of households and people can provide an important background against which to improve individual disaster risk awareness and preparedness–with the final aim of making society, households and individuals more resilient. In this paper, the results of a household survey carried out in eight townships of Yangon (Myanmar) are presented. The analysis investigates how socio-demographic characteristics and the previous experiences of disaster of the respondents and their households influence their disaster risk perception and preparedness in different areas of Yangon City. The results show strong differences in disaster risk perception and preparedness according to socio-demographic characteristics and previous experiences of disaster in different areas of Yangon City …

Erdkunde

Shrub dendrochronology is gaining increasing momentum in temperate high mountain regions to decipher climatic controls on current shrub expansion. Yet, a lack of consensus still persists in terms of sampling protocols, thus hampering comparability of results from different studies. For instance, serial sectioning, i.e. the sampling of multiple sections along the same shrub stem is recommended as it increases the detection of partial and missing rings, but has only been employed in few studies as it is time-consuming. Similarly, as a result of serial sectioning, chronologies frequently combine sections sampled at different positions along the stem and at the root collar which hinders the detection of climatic signals. Here, we used cross-sections sampled on 21 Rhododendron ferrugineum shrubs from the French Pyrenees to define a parsimonious protocol enabling detection of partial and missing rings while increasing …